Statista reveals that companies worldwide leverage an average of 110 SaaS apps. Another report states that the international SaaS industry will cross $700 billion by 2030.
All these numbers point to the increasing demand for software as a service and the growing opportunities for SaaS businesses to thrive. However, the massive competition in the industry makes it challenging for SaaS marketers to gain an edge over more resourced and established brands.
According to McKinsey, despite the industry's image as a bastion of hypergrowth, few businesses sustain growth rates above 30-40%.
In short, the SaaS industry offers solid growth opportunities, but to hit the revenue goals, marketers need to up their marketing performance by leveraging "data." They need in-depth insights to gauge the potential of existing SaaS strategies, identify the gaps, and make an actionable plan to present to the C-suite and achieve revenue goals.
This post will share how the marketing analytics process can help SaaS marketers maximize their revenue. First, let's understand marketing analytics in detail.
What Is Marketing Analytics?
The biggest challenge that SaaS marketers face is collecting and analyzing customer data spread across channels. This often impacts data quality, leading to poor decision-making and unaccomplished SaaS revenue goals.
In a Forrester survey, 21% of respondents reported wasting marketing budgets (1 in 5 dollars lost) because of poor data quality. Hence, businesses need tools and technologies to process and maintain quality data for accurate decision-making.
Marketing analytics is one of the best methods to eliminate shared data-related challenges and establish the value of a campaign to the C-suite.
Marketing analytics consists of processes and technology that enable marketers to collect and analyze data accurately, such as customer behavior, revenue from past marketing campaigns, and more, to predict and accomplish desired revenue goals.
It mainly leverages advanced machine learning algorithms to track SaaS trends, identify revenue opportunities and build a scalable marketing framework. This can help marketers present data-driven insights to the C-suite on optimizing the return on marketing investment and earning high-profit margins.
What Is Its Significance?
Marketing analytics can help SaaS marketers answer vital questions, such as -
- How did the SaaS strategies perform historically?
- How is your existing SaaS marketing strategy performing?
- How is your marketing strategy compared to the competitors?
- What can you do to improve SaaS marketing and boost revenue?
- What aspects need more resources and investment?
With these insights, they can establish and accomplish SMART (Specific, Measurable, Achievable, Realistic, and Time-bound) revenue goals.
Say a SaaS marketer uses marketing analytics to get the findings shared below -
How to Use Marketing Analytics
Now that you've understood marketing analytics, let's focus on how SaaS marketers can reap the best business benefits using it.
1. Generate Accurate Past Events Reports
As discussed earlier, analyzing past events is crucial for SaaS marketers. Here's the workflow that SaaS marketers follow to plan their marketing strategy.
- Analyze past data and create a SaaS marketing strategy
- Run it for a specific timeframe
- Measure the KPIs
- Plan a strategy for the future
For accurate analysis, tracking the right KPIs aligning with the revenue goals is pivotal to generating the desired results. With marketing analytics, SaaS marketers can decide on valuable KPIs that can help assess the impact of their efforts on various marketing channels and develop apt budget spending tactics for the future.
For instance, they can track and create reports on customer acquisition cost (CAC), customer lifetime value (LTV), return on ad spend (ROAS), and more. This gives a clear picture of the past and helps SaaS marketers make data-driven decisions.
2. Analyze the Present Marketing Strategy
With advanced marketing analytics tools, SaaS marketers can access timely, vital information, such as customer behavior, ongoing SaaS trends, current budget spending, and more.
For instance, they can figure out -
- Why is organic traffic to the website decreasing?
- How many customers use the [feature] of our SaaS product?
- What is the website's current ranking for [SaaS query] in Google?
Wondering what the critical output of the marketing analytics process is? With these insights on the present state of affairs combined with past event reports, SaaS marketers can predict the future accurately and take actionable steps to overcome potential challenges and achieve revenue goals.
3. Prove Positive ROI to the C-Suite
Forecasting future revenue goals based on data-driven marketing strategies can help SaaS marketers and chief marketing officers or CMOs prove positive business outcomes to the C-suite and get desired marketing budget.
With advanced marketing analytics models like predictive and prescriptive analytics, marketers can enter the realm of accurate data-driven analysis. With predictive analytics, marketers can figure out - "what will happen?" On the other hand, prescriptive analytics can help them understand "what needs to be done to achieve revenue goals?"
Here's an example:
As you can see, these advanced marketing analytics processes can help marketers build and execute targeted marketing campaigns and strategies.
4. Compare Your Strategies with Competitors
Next, leverage advanced marketing analytics processes to compare your strategies with your competitors.
Use tools like Semrush or Ahrefs to analyze your competitor's content strategy. Use this data to identify and rectify your content gaps. This can help outsmart your competitors in the SaaS landscape.
Four-Step Marketing Analytics Process
In this section, we will explain the steps of the marketing analytics process. Use the below-shared four-step advanced marketing analytics process to improve the effectiveness of your SaaS marketing campaign and increase revenue growth.
Let's get started.
1. Define Your Goals
The first step in the four-step marketing analytics planning process is to define revenue goals.
As discussed, marketing analytics can help you track and achieve revenue goals. However, for precise output, create a marketing analytics process map first. So, begin with defining the valuable revenue metrics you want to assess.
Here are a few key revenue metrics (output metrics) to consider.
- Customer Acquisition Cost (CAC): It reflects the overall marketing and sales expense that SaaS marketers need to acquire a new client.
- Customer Lifetime Value (LTV): This metric estimates a SaaS organization's profitability throughout customer relationships. Increasing LTV allows SaaS marketers to boost customer satisfaction and retention.
- Return on Ad Spend (ROAS): This metric measures your SaaS organization's revenue earned per dollar spent on advertising.
- Revenue Forecasting: It estimates the potential revenue that a firm can generate over a specific timeframe (quarterly or annually).
However, before monitoring these output metrics, it’s crucial to track a few input metrics that are leading indicators of the output. Input metrics are the actions that SaaS marketers can control. They reflect milestones that make the goals actionable.
Check out the following table depicting the input metrics. It defines the controllable actions and the output metrics representing the desired end goals.
Defining input and output metrics can thus help SaaS marketers create a solid goal-setting framework or OKRs (objectives and key results) to track the effectiveness of their efforts.
- Objective - What is the end goal?
- Key Result - What initiatives can help accomplish the end goal?
For example, consider the first use case where the marketer wants to improve the ad quality score. Here, they can define relevant input for output metrics and create a goal-setting framework, as shared below.
- Objective: Improve ad quality score (output metric)
- Key Results: Ad CTR, ad relevance, ad landing page experience (input metrics)
This OKR visual affirms how controlling input metrics can help SaaS marketers achieve the end goal.
As a marketer, defining input metrics is something you can control as they drive the desired revenue goals.
Finally, identifying quality input metrics consumes time and is an iterative process. They may change as you upgrade your services and products. So, make sure you revisit your input metrics frequently to achieve the set output.
2. Analyze Customer Data
Once you have a marketing analytics process map, ensure that your customer data is up-to-date and error-free.
Data inaccuracy or misinterpretation can lead to poor results. Hence, customer data extraction, which is considered the most difficult step in the marketing analytics strategy process, should be done carefully. Research states that inaccurate data can lead to poor outcomes and cost companies up to 12% in revenue per year.
So, analyze your customer data to eliminate old, duplicate, inaccurate, and incomplete data entries.
Pro Tip: Count on customer relationship management systems (CRM) like Zoho CRM or Zendesk to manage, track, and organize customer data and interactions. In addition, these CRM can help segment consumer information into groups according to their demographics, interests, behaviors, purchase history, and more.
This allows marketers to create and target an ideal customer profile (ICP) and increase revenue growth opportunities.
3. Integrate Advanced Marketing Analytics Methods
Advanced marketing analytics can help SaaS marketers use existing data to predict and influence future revenue outcomes. It uses AI and machine learning algorithms to help marketers gauge customer behavior, identify ideal customer profiles (ICP), predict customer churn, evaluate LTV, and more.
The key types of advanced marketing analytics comprise -
- Descriptive Analytics: This marketing analytics uses data to provide insights into past marketing campaigns. This information can help SaaS marketers understand past marketing performance and provide context for understanding marketing data (present).
- Predictive Analytics: As discussed, this method analyzes a large volume of data and helps marketers accurately predict revenue outcomes.
- Prescriptive Analytics: As mentioned earlier, it provides actionable tips and recommendations on reaching revenue goals.
There are hundreds of BI and marketing analytics tools available in the market. However, these tools are more concerned with descriptive analytics. On the other hand, a revenue marketing platform like Revlitix leverages predictive and prescriptive analytics to offer you the most suitable insights and recommendations.
Also, the platform doesn’t need special technical or analytical skills. Marketers can create tailored dashboards within a few clicks.
This state-of-the-art platform automates the countless hours of ad hoc analysis and makes it easy for everyone in the team to collaborate and execute tasks.
Unlike the plethora of BI tools and ABM software in the market, Revlitix serves as the "master" of your marketing tech stack. It monitors your team's performance and provides insights to the appropriate professional without hassles.
4. Reassess the Strategy
Count on your marketing analytics platform insights to optimize your next SaaS marketing campaign.
Does marketing analytics make a process-driven company? Yes, it does. The key to remember here is that the digital marketing analytics process is not a one-time thing. SaaS marketers should consistently monitor customer behavior and ongoing trends and update their strategies to boost revenue.
Summing Up
The four-step marketing analytics process can help SaaS businesses understand what metrics to measure, identify vital areas of improvement, and strengthen marketing efforts.
When applied holistically, shared marketing analytics tactics can lead to successful marketing campaigns and enhanced customer experience, thereby helping the firm achieve greater profitability and revenue.
